//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="featureFilterCfg">Output feature filter settings</param>
/// <param name="networksCfg">Forecasting networks settings</param>
public ForecastTaskSettings(IFeatureFilterSettings featureFilterCfg,
ForecastNetworksSettings networksCfg = null
)
{
FeatureFilterCfg = (IFeatureFilterSettings)featureFilterCfg.DeepClone();
NetworksCfg = networksCfg == null ? new ForecastNetworksSettings() : (ForecastNetworksSettings)networksCfg.DeepClone();
return;
}
//Constructors
/// <summary>
/// Creates an unitialized instance
/// </summary>
/// <param name="name">The name of the input field.</param>
/// <param name="featureFilterCfg">The configuration of the feature filter associated with the input field.</param>
/// <param name="routeToReadout">Specifies whether to route the input field to the readout layer.</param>
public ExternalFieldSettings(string name,
IFeatureFilterSettings featureFilterCfg,
bool routeToReadout = DefaultRouteToReadout
)
{
Name = name;
FeatureFilterCfg = (IFeatureFilterSettings)featureFilterCfg.DeepClone();
RouteToReadout = routeToReadout;
Check();
return;
}
/// <summary>
/// Instantiates the appropriate feature filter.
/// </summary>
/// <param name="outputRange">The output range of the feature filter.</param>
/// <param name="cfg">The feature filter configuration.</param>
public static FeatureFilterBase Create(Interval outputRange, IFeatureFilterSettings cfg)
{
switch (cfg.Type)
{
case FeatureFilterBase.FeatureType.Binary:
return(new BinFeatureFilter(outputRange, (BinFeatureFilterSettings)cfg));
case FeatureFilterBase.FeatureType.Real:
return(new RealFeatureFilter(outputRange, (RealFeatureFilterSettings)cfg));
default:
throw new ArgumentException($"Unexpected feature type {cfg.Type}", "settings");
}
}
//Constructor
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="name">The name of the input field.</param>
/// <param name="idx">The zero-based index of the input field among other input fields.</param>
/// <param name="coordinates">The coordinates of input neurons in 3D space.</param>
/// <param name="dataWorkingRange">The output range of the input data.</param>
/// <param name="featureFilterCfg">The configuration of the feature filter.</param>
/// <param name="spikesEncodingCfg">The configuration of the spikes coder.</param>
/// <param name="routeToReadout">Specifies whether to route the input field values to readout layer.</param>
/// <param name="inputNeuronsStartIdx">The zero-based index of the first input neuron of this field among all other input neurons.</param>
public InputField(string name,
int idx,
int[] coordinates,
Interval dataWorkingRange,
IFeatureFilterSettings featureFilterCfg,
InputSpikesCoderSettings spikesEncodingCfg,
bool routeToReadout,
int inputNeuronsStartIdx
)
{
Name = name;
Idx = idx;
RouteToReadout = routeToReadout;
_featureFilter = FeatureFilterFactory.Create(dataWorkingRange, featureFilterCfg);
_iAnalogStimuli = 0;
_currentDataIdx = 0;
//Spikes encoder
_spikesEncoder = new InputSpikesCoder(spikesEncodingCfg);
//Analog neuron
int verticalCycles = _spikesEncoder.Regime == InputEncoder.InputSpikesCoding.Vertical ? _spikesEncoder.LargestComponentLength : 1;
AnalogNeuron = new AnalogInputNeuron(new NeuronLocation(InputEncoder.ReservoirID, inputNeuronsStartIdx, InputEncoder.PoolID, inputNeuronsStartIdx, idx, coordinates[0], coordinates[1], coordinates[2]), verticalCycles);
++inputNeuronsStartIdx;
//Spiking neurons
int spikingPopulationSize;
if (_spikesEncoder.Regime == InputEncoder.InputSpikesCoding.Horizontal)
{
//Population encoding
spikingPopulationSize = _spikesEncoder.AllSpikesFlatCollection.Length;
}
else if (_spikesEncoder.Regime == InputEncoder.InputSpikesCoding.Vertical)
{
//Spike-train encoding
spikingPopulationSize = _spikesEncoder.ComponentSpikesCollection.Length;
}
else
{
//Forbidden encoding
spikingPopulationSize = 0;
}
SpikingNeuronCollection = new SpikingInputNeuron[spikingPopulationSize];
for (int i = 0; i < SpikingNeuronCollection.Length; i++)
{
SpikingNeuronCollection[i] = new SpikingInputNeuron(new NeuronLocation(InputEncoder.ReservoirID, inputNeuronsStartIdx, InputEncoder.PoolID, inputNeuronsStartIdx, idx, coordinates[0], coordinates[1], coordinates[2]));
++inputNeuronsStartIdx;
}
return;
}
/// <summary>
/// Creates deep copy of given settings
/// </summary>
/// <param name="settings">Settings of feature filter</param>
public static IFeatureFilterSettings DeepClone(IFeatureFilterSettings settings)
{
switch (settings.Type)
{
case FeatureFilterBase.FeatureType.Binary:
return(new BinFeatureFilterSettings((BinFeatureFilterSettings)settings));
case FeatureFilterBase.FeatureType.Enum:
return(new EnumFeatureFilterSettings((EnumFeatureFilterSettings)settings));
case FeatureFilterBase.FeatureType.Real:
return(new RealFeatureFilterSettings((RealFeatureFilterSettings)settings));
default:
throw new ArgumentException($"Unexpected feature type {settings.Type}", "settings");
}
}
//Constructors
/// <summary>
/// Creates an unitialized instance
/// </summary>
/// <param name="name">Input field name</param>
/// <param name="featureFilterCfg">Configuration of feature filter associated with the input field</param>
/// <param name="routeToReadout">Specifies whether to route input field to readout layer together with other predictors</param>
/// <param name="spikeCodeCfg">Configuration of spike code</param>
public ExternalFieldSettings(string name,
IFeatureFilterSettings featureFilterCfg,
bool routeToReadout = DefaultRouteToReadout,
SpikeCodeSettings spikeCodeCfg = null
)
{
Name = name;
FeatureFilterCfg = (IFeatureFilterSettings)featureFilterCfg.DeepClone();
RouteToReadout = routeToReadout;
SpikeCodeCfg = (SpikeCodeSettings)spikeCodeCfg?.DeepClone();
if (featureFilterCfg.Type == FeatureFilterBase.FeatureType.Real && spikeCodeCfg == null)
{
SpikeCodeCfg = new SpikeCodeSettings();
}
Check();
return;
}
//Constructor
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="name">Name of the input field</param>
/// <param name="idx">Index of the input field</param>
/// <param name="coordinates">Input coordinates (entry point)</param>
/// <param name="dataWorkingRange">Input data range</param>
/// <param name="featureFilterCfg">Feature filter configuration</param>
/// <param name="spikeCodeCfg">Configuration of the input spike code</param>
/// <param name="routeToReadout">Specifies whether to route values as the additional predictors to readout</param>
/// <param name="inputNeuronsStartIdx">Index of the first input neuron of this unit among all input neurons</param>
public InputField(string name,
int idx,
int[] coordinates,
Interval dataWorkingRange,
IFeatureFilterSettings featureFilterCfg,
SpikeCodeSettings spikeCodeCfg,
bool routeToReadout,
int inputNeuronsStartIdx
)
{
Name = name;
Idx = idx;
RouteToReadout = routeToReadout;
_featureFilter = FeatureFilterFactory.Create(dataWorkingRange, featureFilterCfg);
//Analog neuron
AnalogNeuron = new AnalogInputNeuron(new NeuronLocation(InputEncoder.ReservoirID, inputNeuronsStartIdx, InputEncoder.PoolID, inputNeuronsStartIdx, idx, coordinates[0], coordinates[1], coordinates[2]));
++inputNeuronsStartIdx;
//Spiking neurons
_realSpikeCode = null;
int populationSize = -1;
switch (_featureFilter.Type)
{
case FeatureFilterBase.FeatureType.Real:
_realSpikeCode = new SpikeCode(spikeCodeCfg);
populationSize = _realSpikeCode.Code.Length;
break;
case FeatureFilterBase.FeatureType.Binary:
populationSize = 1;
break;
case FeatureFilterBase.FeatureType.Enum:
populationSize = ((EnumFeatureFilterSettings)featureFilterCfg).NumOfElements;
break;
}
SpikingNeuronCollection = new SpikingInputNeuron[populationSize];
for (int i = 0; i < SpikingNeuronCollection.Length; i++)
{
SpikingNeuronCollection[i] = new SpikingInputNeuron(new NeuronLocation(InputEncoder.ReservoirID, inputNeuronsStartIdx, InputEncoder.PoolID, inputNeuronsStartIdx, idx, coordinates[0], coordinates[1], coordinates[2]));
++inputNeuronsStartIdx;
}
return;
}
